• Microbiology and Biotechnology Letters
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• v.33 no.2
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• pp.148-153
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• 2005

Malaria is a re-emerging infectious disease that is spreading to areas where it had been eradicated, such as Eastern Europe and Central Asia. To avoid the mortality from malaria, early detection of the parasite is a very important issue. The peripheral blood smear has been the gold standard method for the diagnosis of malaria infection. Recently, several other methods have been introduced for quantitative detection of malaria parasites. Real time PCR that employs fluorescent labels to enable the continuous monitoring of PCR product formation throughout the reaction has recently been used to detect several human malaria parasites. 18S rRNA sequences from malaria parasites have been amplified using Taqman real time PCR assay. Here, a SYBR Green-based real time quantitative PCR assay for the detection of malaria parasite-especially, Plasmodium vivax - was applied for the evaluation of 26 blood samples from Korean malaria patients. Even though SYBR Green-based real time PCR is easier and cheaper than Taqman-based assay, SYBR Green-based assay cannot be used because 18S rRNA cannot be specifically amplified using 1 primer set. Therefore, we used DBP gene sequences from Plasmodium vivax, which is specific for the SYBR Green based assays. We amplified the DBP gene from the 26 blood samples of malaria patients using SYBR Green based assay and obtained the copy numbers of DBP genes for each sample. Also, we selected optimal reference gene between ACTB and B2M using real time assay to get the stable genes regardless of Malaria titer. Using selected ACTB reference genes, we successfully converted the copy numbers from samples into titer, ${\sharp}$ of parasites per microliter. Using the resultant titer from DBP based SYBER Green assay with ACTB reference gene, we compared the results from our study with the titer from Taqman-based assay. We found that our results showed identical tendency with the results of 18S rRNA Taqman assay, especially in lower titer range. Thus, our DBP gene-utilized real time assay can detect Plasmodium vivax in Korean patient group semi-quantitatively and easily.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.329-332
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• 1991

This paper presents an algorithm to reduce the time to solve Power Equations using a Neural Net. The Neural Net is trained with samples obtained through the conventional AC Load Flow. With these samples, the Neural Net is constructed and has the function of a linear interpolation network. Given arbitrary load level, this Neural Net generates voltage magnitudes and angles which are linear interpolation of real and reactive powers. Obtained voltage magnitudes and angles are substituted to Power Equations, Real and reactive powers are found. Thus, a new sample is generated. This new experience modifies weight matrix. Continuing to modify the weight matrix, the correct solution is achieved. comparing this method with AC Load flow, this method is faster. If we consider parallel processing, this method is far faster than conventional ones.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.517-524
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• 1998

This paper discusses the development of a reactive power controller using digital signal processing. Digital Signal Processing is the technique of using digital devices to Process continuous signals or data, often in real-time. And DSP algorithms are associated with a discrete time interval between input samples. When one designs a digital filter, one can use a Laplace transform to determine the continuous time frequency response. The corresponding discrete time transform is called Z transform and depends upon discrete samples of the input spaced equally in time. The objectives of this paper are to minimize real power losses and improve the power factor of a given system. Also, the implementation of a direct-form non recursive filter on the TMS320C31 has been described. The application of this microprocessor-based controller using DSP on test system reveals its numerous advantages. Performance and features of the controller for the reactive power control are analyzed.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.234-243
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• 2017

With the development of smartphone technologies enable photoplethysmogram (PPG) acquisition by camera and heart rate (HR) measurement. This papers presents improved algorithm to extract HR from PPG signal recorded by smartphone camera and to develop real-time PPG signal processing Android application. 400 video samples recorded by Samsung smartphone camera are imported as input data for further processing and evaluating algorithm on MATLAB. An optimized algorithm is developed and tested on Android platform with different kind of Samsung smartphones. To assess algorithm's performance, medical device Beurer BC08 is used as reference. According to related works, accuracy parameters includes 90% number of samples that has relative errors less than 5%, Person correlation (r) more than 0.9, and standard estimated error (SEE) less than 5 beats-per-minutes (bpm).

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1582-1590
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• 2022

Due to the situation of the widespread of the coronavirus, which causes the problem of lack of face image data occluded by masks at recent time, in order to solve the related problems, this paper proposes a method to generate face images with masks using a combination of generative adversarial networks and spatial transformation networks based on CNN model. The system we proposed in this paper is based on the GAN, combined with multi-scale convolution kernels to extract features at different details of the human face images, and used Wasserstein divergence as the measure of the distance between real samples and synthetic samples in order to optimize Generator performance. Experiments show that the proposed method can effectively put masks on face images with high efficiency and fast reaction time and the synthesized human face images are pretty natural and real.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.7
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• pp.4209-4214
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• 2013

Background: Breast cancer is among the five most common cancers and ranks first among cancers diagnosed in Iranian women. Screening and treatment of this disease with molecular methods, especially regarding high incidences at early age and advanced stage, is essential. Several genes with altered expression have been identified by cDNA microarray studies in breast cancer, with the Bcl-2 gene indicated as a likely candidate. In this study, we studied Bcl-2 gene expression levels in parallel tumor and non-tumor breast tissues. Materials and Methods: Forty samples including 21 tumor, 16 non tumor (marginal) and 3 benign breast tissues which were all pathologically diagnosed, were subjected to RNA extraction and polyA RT-PCR with the expression level of Bcl-2 quantified using real-time PCR. Results: There is higher expression levels of the Bcl-2 gene in tumor samples compared with marginal samples, but not attaining significance(p>0.05). Bcl-2 expression in 14 (66.7%) of the cases of tumor samples and 9 (56.3%) cases of the marginal samples were positive. Comparison of the expression of the Bcl-2 gene in histological grade showed that a high expression of Bcl-2 was associated with a high histological grade (p<0.41). Conclusions: Our data suggests that dysregulated Bcl-2 gene expression is potentially involved in the pathogenesis of breast cancer. Using gene expression analysis may significantly improve our ability for screening cancer patients and will prove a powerful tool in the diagnosis and prognostic evaluation of the disease whilst aiding the cooperative group trials in the Bcl-2 based therapy project.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• Journal of Acupuncture Research
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• v.35 no.3
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• pp.104-107
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• 2018

Background: Reduced impedance at acupuncture points (acupoints) is a well-known phenomenon; and the impedance has been found to reduce further in relation to organ stress. The author hypothesises that any changes to an organ's state or function are communicated to its related acupoints in real time. As part of a research project to demonstrate this communication, the impedance of several acupoints was studied in real time. Methods: The acupoints were located electrically, and a 40 kHz signal was used to sample the impedances. Samples were taken at each acupoint and also at a 6 mm radius. The sample rate was 1 kHz and the session lasted for 5 minutes. The results presented here were taken from a single patient. Results: The impedance at an acupoint's centre frequently changed in an inverse relationship to the impedance at a 6 mm radius (i.e. when one goes up, the other goes down) and the left and right instance of the same acupoint usually displayed different impedance features. Conclusion: When studying the fine detail of real-time impedance samples taken from the centre of an acupoint and also from a 6 mm radius, this previously unreported contrary-motion phenomenon provides a useful tool to differentiate between artefact and genuine organ-related features in an impedance trace.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3953-3958
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• 2016

Prostatic cancer is the second cause of cancer-related death among men worldwide. The human papilloma viruses (HPVs) are a family of sexually transmitted viruses which have may have roles in the ethiology of inflammation in prostate leading to benign prostatic hyperplasia (BPH) and prostate cancer (PCa). In this study, we evaluated the frequency of different HPV types in prostatic cancer and benign prostatic hyperplasia (BPH) in Kerman province, southeast of Iran, using real-time PCR techniques. The aim of the present research was to clarify any association with prostatic carcinogenesis. Real Time PCR showed that HPV DNA was found in 20% of 200 PCa samples, 80 percent of these with high-risk HPV types, 40% with type-16,18, 30 % type-31,33 and 10% type 54. High risk HPV DNA was detected in only 2% of BPH samples. Values for low risk types were much higher. Our study provided a support for the role of high risk HPV infection in prostatic disease in Iranian patients, and association between presence of HPV DNA and prostate carcinoma. In particular, HPV 16 and18 might have an important role in prostate cancer.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.339-353
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• 2014

A straightforward method for optimal determining of a high frequency inductor's parasitic capacitance is presented. The proposed estimation method is based on measuring the inductor's impedance samples over a limited frequency range bordering on the resonance point considering k-dB deviation from the maximum impedance. An optimized solution to k could be obtained by minimizing the root mean squared error between the measured and the estimated impedance values. The model used to provide the estimations is a parallel RLC circuit valid at resonance frequency which will be transferred to the real model considering the mentioned interval of frequencies. A straightforward algorithm is suggested and programmed using MATLAB which does not require a wide knowledge of design parameters and could be implemented using a spectrum analyzer. The inputs are the measured impedance samples as a function of frequency along with the diameter of the conductors. The suggested algorithm practically provides the estimated parameters of a real inductance model at different frequencies, with or without design information. The suggested work is different from designing a high frequency inductor; it is rather concentration of determining the parameters of an available real inductor that could be easily done by a recipe provided to a technician.